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pabandi_book_stay

Create a confirmed stay reservation for a property: links the existing Reservation model + a StayBooking, then holds the guest deposit in escrow (EscrowEvent + TreasuryPosition with kind:hospitality, Solana commitment, PTP attestation). The guest deposit is the trust anchor — released to the business on check-in, refunded on cancellation. This is the hospitality money rail. [verified] Gated to businesses with an attested open-finance settlement rail OR PTP Band A/B, so every booked stay has a real, verified payout path. This is what makes the hospitality vertical trustworthy to guests and exclusive to quality hosts. This MCP tool makes a real HTTP call to the canonical Pabandi endpoint and returns the actual platform response.

Input Schema

NameRequiredDescriptionDefault
guestsYesnumber of guests (optional)
checkInYesISO date
checkOutYesISO date
propertyIdYesproperty id
depositAmountYesguest deposit to hold (optional, defaults to 1 night)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and discloses key behavioral traits: this is a write operation that creates a booking, holds a deposit in escrow, releases on check-in, refunds on cancellation, and is gated by settlement/PTP criteria. It still omits idempotency, permission/error behavior, and what happens on partial failures.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded, but the description contains marketing language and internal implementation jargon such as 'hospitality money rail' and 'exclusive to quality hosts' that do not help an agent invoke the tool. It is usable but not tight.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex money-moving mutation with no annotations and no output schema, the description covers the deposit lifecycle and gating well. It still lacks return-value expectations beyond 'actual platform response', error handling, and idempotency guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds some meaning around depositAmount by framing the guest deposit as a held trust anchor, but it does not clarify the other parameters, and it does not resolve the schema's own 'optional' annotations on required fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific action and resource: creating a confirmed stay reservation for a property, including deposit escrow. It does not explicitly distinguish itself from siblings like pabandi_predict_booking or pabandi_start_escrow, so sibling differentiation is weak.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a real usage condition: the business must have an attested open-finance settlement rail or PTP Band A/B. However, it does not state when to use this tool versus alternatives such as pabandi_start_escrow or pabandi_predict_booking, leaving the routing decision mostly implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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